Computer Science

Computer scientists study the inherent complexity of computational problems, and design efficient algorithms to solve them. At Denison, we emphasize the enduring core principles of computer science, and how they can be applied to a vast array of interdisciplinary problems in the natural and social sciences, and the arts.

Research

Faculty Research Interests

Algorithms, computational biology

I enjoy designing efficient online algorithms for network and scheduling problems. Like a market speculator, an online algorithm must respond to input as it arrives, without knowing the future. I am also interested in computational biology problems.

Artificial intelligence

My primary research interests are in artificial intelligence and machine learning. I am interested in studying how people learn to solve complex problems and then capturing that same behavior in a computer algorithm.

Big data

My research spans many different areas in computer science related to large data sets. Projects we could work on would involve answering questions about large network traffic, commercial product, or social network data sets.

Complex analysis

I have four manuscripts in various stages of completion that support the teaching of 1) mainstream calculus, 2) advanced calculus, 3) linear algebra, 4) complex analysis. Each small book is not a textbook but is a book (approximately 100 pages) that I believe will be useful to students, teachers, and professors.

Computer systems

My research interests are within the systems area of computer science and can be partitioned into the subareas of (i) fault-tolerance, (ii) networking and inter-domain routing, and (iii) high performance computing.

Formal methods

My research lies in the field of formal methods for software engineering. The focus is on the formal specification of software in the context of software engineering principles developed by experts in the field over decades of research and practice.

Operator algebras, statistical modeling

I study operator algebras and statistical modeling. Operator algebras generalize problems in virtually every undergraduate class and model observable quantities in quantum physics. My statistical work is concerned with player evaluation in the NBA.

Interested students should directly contact faculty to inquire about opportunities for summer research, senior research, or independent studies.

Thomas Bressoud worked outside of academia both before and after receiving his Ph.D. from Cornell University in 1996. Before his time in Ithaca, Dr. Bressoud spent 7 years working for MIT Lincoln Laboratory in real-time radar systems. After his Ph.D., Dr. Bressoud worked for a startup, Isis Distributed Systems, and, through the acquisition frenzy of the 90’s, was working for Lucent Technologies when he transferred to their research arm, Bell Laboratories in Murray Hill, NJ.

In 2002, Dr. Bressoud joined the Denison faculty. He enjoys teaching courses across the undergraduate curriculum, from introductory courses exposing students from across campus to the fundamental ideas of computer science to upper level electives. In alignment with his research interests, he particularly enjoys teaching systems classes, like Networking and Operating Systems, and a special topics course in parallel programming and high performance systems.